This position is commonly defended for consequentialist arguments for vegetarianism and veganism; see, e.g., Section 2 here, Section 2 here, and especially Day 2 here. The argument usually goes something like: if you stop buying one person’s worth of eggs, then in expectation, the industry will not produce something like one pound of eggs that they would’ve produced otherwise. Even if you are not the tipping point to cause them to cause production, due to uncertainty you still have positive expected impact. (I’m being a bit vague here, but I recommend reading at least one of the above readings—especially the third one—because they make the argument better than I can.)
In the case of animal product consumption, I’m confused what you mean by “the expected impact still remains negligible in most scenarios”—are you referring to different situations? I agree in principle that if the expected impact is tiny, then we don’t have much reason on consequentialist grounds to avoid the behavior, but do you have a particular situation in mind? Can you give concrete examples of where your shift in views applies/where you think the reasoning doesn’t apply well?
One of those sources (“Compassion, by the Pound”) estimates that reducing consumption by one egg results in an eventual fall in production by 0.91 eggs, i.e., less than a 1:1 effect.
I’m not arguing against the idea that reducing consumption leads to a long-term reduction in production. I’m doubtful that we can meaningfully generalise this kind of reasoning across different specifics as well as distinct contexts without investigating it practically.
For example, there probably exist many types of food products where reducing your consumption only has like a 0.1:1 effect. (It’s also reasonable to consider that there are some cases where reducing consumption could even correspond with increased production.) There are many assumptions in place that might not hold true. Although I’m not interested in an actual discussion about veganism, one example of a strong assumption that might not be true is that the consumption of egg is replaced by other food sources that are less bad to rely on.
I’m thinking that the overall “small chance of large impact by one person” argument probably doesn’t map well to scenarios where voting is involved, one-off or irregular events, sales of digital products, markets where the supply chain changes over time because there’s many ways to use those products, or where excess production can still be useful. When I say “doesn’t map well”, I mean that the effect of one person taking action could be anywhere between 0:1 to 1:1 compared to what happens when the sufficient number of people simultaneously make the change in decision-making required for a significant shift. If we talk about one million people needing to vote differently so that a decision is reversed, the expected impact of my one vote is always going to be less than 100% of one millionth, because it’s not guaranteed that one million people will sway their vote. If there’s only a 10% chance of the one million swayed votes, I’d think my expected impact to come out at far less than even 0.01:1 from a statistical model.
I agree that this style of reasoning depends heavily on the context studied (in particular, the mechanism at play), and that we can’t automatically use numbers from one situation for another. I also agree with what I take to be your main point: In many situations, the impact is less than 1:1 due to feedback loops and so on.
I’m still not sure I understand the specific examples you provide:
Animal products used as food: For commonly-consumed food animal products, I would be surprised if the numbers were much lower than those in the table from Compassion by the Pound (assuming that those numbers are roughly correct). This is because the mechanism used to change levels of production is similar in these cases. (The previous sentence is probably naive, so I’m open to corrections.) However, your point about substitution across goods (e.g., from beef to chicken) is well taken.
Other animal products: Not one of the examples you gave, but one material that’s interested me is cow leather. I’m guessing that (1) much of leather is a byproduct* of beef production and (2) demand for leather is relatively elastic. Both of these suggest that abstaining from buying leather goods has a fairly small impact on farmed animal welfare suffering.**
Voting: I am unsure what you mean here by “1:1”. Let me provide a concrete example, which I take to be the situation you’re talking about. We have an election with n voters and 2 candidates, with the net benefit of the better candidate winning U. If all voters were to vote for the better candidate, then each person’s average impact is U / n. I assume that this is what you mean by the “1″ in “1:1”: if someone has expected counterfactual impact U / n, then their impact is 1:1. If this is what you mean by 1:1, then actually one’s impact can easily be greater than U / n, going against your claim. For example, if your credence on the better candidate winning is exactly 50%, then U / n is a lower bound; see Ord (2023), some of whose references show that in real-world situations, the probability of swaying the election can be much greater than 1 / n.
* Not exactly a byproduct, since sales of leather increases the revenue from raising a cow. ** This is not accounting for less direct impacts on demand, like influencing others around oneself.
This is because the mechanism used to change levels of production is similar in these cases.
I’m unclear on the exact mechanism and suspect that the anecdote of “the manager sees the reduced demand across an extended period and decides to lower their store’s import by the exact observed reduction” is a gross oversimplification of what I would have guessed is a complex system where the manager isn’t perfectly rational, may have long periods without review due to contractual reasons, the supply chain lasting multiple parties all with non-linear relationships. Maybe some food supply chains significantly differ at the grower’s end, or in different countries. My missing knowledge here is why I don’t think I have a good reason to assume generality.
Other animal products
I think your cow leather example highlights the idea that for me threatens simplistic math assumptions. Some resources are multi-purpose, and can be made into different products through different processes and grades of quality depending on the use case. It’s pretty plausible that eggs are either used for human consumption or hatching. Some animal products might be more complicated and be used for human consumption or non-human consumption or products in other industries. It seems reasonable for me to imagine a case where decreasing human consumption results in wasted production which “inspires” someone to redirect that production to another product/market which becomes successful and results in increased non-dietary demand. I predict that this isn’t uncommon and could dilute some of the marginal impact calculations which are true short-term but might not play out long-term. (I’m not saying that reducing consumption isn’t positive expectation, I’m saying that the true variance of the positive could be very high over a long-term period that typically only becomes clear in retrospect.)
Voting
Thanks for that reference from Ord. I stand updated on voting in elections. I have lingering skepticism about a similar scenario that’s mathematically distinct: petition-like scenarios. E.g. if 100k people sign this petition, some organization is obliged to respond. Or if enough students push back on a school decision, the school might reconsider. This is kind of like voting except that the default vote is set. People who don’t know the petition exists have a default vote. I think the model described by Ord might still apply, I just haven’t got my head around this variation yet.
I agree that the simple story of a producer reacting to changing demand directly is oversimplified. I think we differ in that I think that absent specific information, we should assume that any commonly consumed animal product’s supply response to changing demand should be similar to the ones from Compassion, by the Pound. In other words, we should have our prior on impact centered around some of the numbers from there, and update from there. I can explain why I think this in more detail if we disagree on this.
Leather example:
Sure, I chose this example to show how one’s impact can be diluted, but I also think that decreasing leather consumption is unusually low-impact. I don’t think the stories for other animal products are as convincing. To take your examples:
Eggs for human consumption are unfertilized, so I’m not sure how they are useful for hatching. Perhaps you are thinking that producers could fertilize the eggs, but that seems expensive and wouldn’t make sense if demand for eggs is decreasing.
Perhaps I am uncreative, but I’m not sure how one would redirect unused animal products in a way that would replace the demand from human consumption. Raising an animal seems pretty expensive, so I’m not sure in what scenario this would be so profitable.
If we are taking into account the sort of “meta” effects of consuming fewer animal products (such as your example of causing people to innovate new ways of using animal products), then I agree that these increase the variance of impact but I suspect that they strongly skew the distribution of impact towards greater rather than lesser impact. Some specific, and straightforward, examples: companies research more alternatives to meat; society has to accommodate more vegans and vegan food ends up more widespread and appealing, making more people interested in the transition; people are influenced by their reducetarian friends to eat less meat.
Voting:
I’ll need to think about it more, but as with two-candidate votes, I think that petitions can often have better than 1:1 impact.
This position is commonly defended for consequentialist arguments for vegetarianism and veganism; see, e.g., Section 2 here, Section 2 here, and especially Day 2 here. The argument usually goes something like: if you stop buying one person’s worth of eggs, then in expectation, the industry will not produce something like one pound of eggs that they would’ve produced otherwise. Even if you are not the tipping point to cause them to cause production, due to uncertainty you still have positive expected impact. (I’m being a bit vague here, but I recommend reading at least one of the above readings—especially the third one—because they make the argument better than I can.)
In the case of animal product consumption, I’m confused what you mean by “the expected impact still remains negligible in most scenarios”—are you referring to different situations? I agree in principle that if the expected impact is tiny, then we don’t have much reason on consequentialist grounds to avoid the behavior, but do you have a particular situation in mind? Can you give concrete examples of where your shift in views applies/where you think the reasoning doesn’t apply well?
One of those sources (“Compassion, by the Pound”) estimates that reducing consumption by one egg results in an eventual fall in production by 0.91 eggs, i.e., less than a 1:1 effect.
I’m not arguing against the idea that reducing consumption leads to a long-term reduction in production. I’m doubtful that we can meaningfully generalise this kind of reasoning across different specifics as well as distinct contexts without investigating it practically.
For example, there probably exist many types of food products where reducing your consumption only has like a 0.1:1 effect. (It’s also reasonable to consider that there are some cases where reducing consumption could even correspond with increased production.) There are many assumptions in place that might not hold true. Although I’m not interested in an actual discussion about veganism, one example of a strong assumption that might not be true is that the consumption of egg is replaced by other food sources that are less bad to rely on.
I’m thinking that the overall “small chance of large impact by one person” argument probably doesn’t map well to scenarios where voting is involved, one-off or irregular events, sales of digital products, markets where the supply chain changes over time because there’s many ways to use those products, or where excess production can still be useful. When I say “doesn’t map well”, I mean that the effect of one person taking action could be anywhere between 0:1 to 1:1 compared to what happens when the sufficient number of people simultaneously make the change in decision-making required for a significant shift. If we talk about one million people needing to vote differently so that a decision is reversed, the expected impact of my one vote is always going to be less than 100% of one millionth, because it’s not guaranteed that one million people will sway their vote. If there’s only a 10% chance of the one million swayed votes, I’d think my expected impact to come out at far less than even 0.01:1 from a statistical model.
Thanks, this makes things much clearer to me.
I agree that this style of reasoning depends heavily on the context studied (in particular, the mechanism at play), and that we can’t automatically use numbers from one situation for another. I also agree with what I take to be your main point: In many situations, the impact is less than 1:1 due to feedback loops and so on.
I’m still not sure I understand the specific examples you provide:
Animal products used as food: For commonly-consumed food animal products, I would be surprised if the numbers were much lower than those in the table from Compassion by the Pound (assuming that those numbers are roughly correct). This is because the mechanism used to change levels of production is similar in these cases. (The previous sentence is probably naive, so I’m open to corrections.) However, your point about substitution across goods (e.g., from beef to chicken) is well taken.
Other animal products: Not one of the examples you gave, but one material that’s interested me is cow leather. I’m guessing that (1) much of leather is a byproduct* of beef production and (2) demand for leather is relatively elastic. Both of these suggest that abstaining from buying leather goods has a fairly small impact on farmed animal welfare suffering.**
Voting: I am unsure what you mean here by “1:1”. Let me provide a concrete example, which I take to be the situation you’re talking about. We have an election with n voters and 2 candidates, with the net benefit of the better candidate winning U. If all voters were to vote for the better candidate, then each person’s average impact is U / n. I assume that this is what you mean by the “1″ in “1:1”: if someone has expected counterfactual impact U / n, then their impact is 1:1. If this is what you mean by 1:1, then actually one’s impact can easily be greater than U / n, going against your claim. For example, if your credence on the better candidate winning is exactly 50%, then U / n is a lower bound; see Ord (2023), some of whose references show that in real-world situations, the probability of swaying the election can be much greater than 1 / n.
* Not exactly a byproduct, since sales of leather increases the revenue from raising a cow.
** This is not accounting for less direct impacts on demand, like influencing others around oneself.
I’m unclear on the exact mechanism and suspect that the anecdote of “the manager sees the reduced demand across an extended period and decides to lower their store’s import by the exact observed reduction” is a gross oversimplification of what I would have guessed is a complex system where the manager isn’t perfectly rational, may have long periods without review due to contractual reasons, the supply chain lasting multiple parties all with non-linear relationships. Maybe some food supply chains significantly differ at the grower’s end, or in different countries. My missing knowledge here is why I don’t think I have a good reason to assume generality.
Other animal products
I think your cow leather example highlights the idea that for me threatens simplistic math assumptions. Some resources are multi-purpose, and can be made into different products through different processes and grades of quality depending on the use case. It’s pretty plausible that eggs are either used for human consumption or hatching. Some animal products might be more complicated and be used for human consumption or non-human consumption or products in other industries. It seems reasonable for me to imagine a case where decreasing human consumption results in wasted production which “inspires” someone to redirect that production to another product/market which becomes successful and results in increased non-dietary demand. I predict that this isn’t uncommon and could dilute some of the marginal impact calculations which are true short-term but might not play out long-term. (I’m not saying that reducing consumption isn’t positive expectation, I’m saying that the true variance of the positive could be very high over a long-term period that typically only becomes clear in retrospect.)
Voting
Thanks for that reference from Ord. I stand updated on voting in elections. I have lingering skepticism about a similar scenario that’s mathematically distinct: petition-like scenarios. E.g. if 100k people sign this petition, some organization is obliged to respond. Or if enough students push back on a school decision, the school might reconsider. This is kind of like voting except that the default vote is set. People who don’t know the petition exists have a default vote. I think the model described by Ord might still apply, I just haven’t got my head around this variation yet.
I agree that the simple story of a producer reacting to changing demand directly is oversimplified. I think we differ in that I think that absent specific information, we should assume that any commonly consumed animal product’s supply response to changing demand should be similar to the ones from Compassion, by the Pound. In other words, we should have our prior on impact centered around some of the numbers from there, and update from there. I can explain why I think this in more detail if we disagree on this.
Leather example:
Sure, I chose this example to show how one’s impact can be diluted, but I also think that decreasing leather consumption is unusually low-impact. I don’t think the stories for other animal products are as convincing. To take your examples:
Eggs for human consumption are unfertilized, so I’m not sure how they are useful for hatching. Perhaps you are thinking that producers could fertilize the eggs, but that seems expensive and wouldn’t make sense if demand for eggs is decreasing.
Perhaps I am uncreative, but I’m not sure how one would redirect unused animal products in a way that would replace the demand from human consumption. Raising an animal seems pretty expensive, so I’m not sure in what scenario this would be so profitable.
If we are taking into account the sort of “meta” effects of consuming fewer animal products (such as your example of causing people to innovate new ways of using animal products), then I agree that these increase the variance of impact but I suspect that they strongly skew the distribution of impact towards greater rather than lesser impact. Some specific, and straightforward, examples: companies research more alternatives to meat; society has to accommodate more vegans and vegan food ends up more widespread and appealing, making more people interested in the transition; people are influenced by their reducetarian friends to eat less meat.
Voting:
I’ll need to think about it more, but as with two-candidate votes, I think that petitions can often have better than 1:1 impact.